The Denial of Governance Failure in High-Trust Democracies

📅 Publication Date 2025-07-20 📝 Description This dataset and accompanying Python notebook support the empirical analysis for the study "The Denial of Governance Failure in High-Trust Democracies". The project investigates how interpersonal trust and informal social norms interact with perceptions of institutional legitimacy and income distribution, using large-scale survey data. The core research question: Do trust-based informal norms mask or reinforce corruption-like mechanisms in high-trust democracies through preferential behavior? Included Files: Controls.xlsx – Demographic and background controls Core.xlsx – Variables on trust, fairness, helpfulness, and informal norms Institutional.xlsx – Institutional trust and confidence indicators Polis.ipynb – Google Colab–ready Python notebook containing full data processing and regression analysis pipeline (OLS with robust and clustered SEs, VIF checks, and visualization). 📂 How to Use in Google Colab Open Google Colab: https://colab.research.google.com Upload Files: Click the folder icon (📁) in the left sidebar Click the upload icon and add the 4 files: Controls.xlsx, Core.xlsx, Institutional.xlsx, Polis.ipynb Open the Notebook: Double-click Polis.ipynb in the file browser to open it Run the Notebook: Follow the step-by-step cells, which load data, clean it, run regressions, compute VIFs, and produce tables and plots You may modify file paths if needed:Replace '/content/Controls.xlsx' with the corresponding uploaded path if you mount Google Drive instead Requirements: The notebook auto-installs required packages: !pip install pandas statsmodels openpyxl 🧾 License Creative Commons Attribution 4.0 International (CC BY 4.0)Copyright (C) 2025 The Authors. 🏷️ Keywords Social capital, corruption, trust, governance, informal norms, OLS regression, high-trust democracies, GSS, inequality, institutional confidence 🌐 Languages English 🧪 Programming Language Python 3.11Notebook-compatible with Google Colab and Jupyter 🏗️ Version v1.0.0 📦 Publisher Zenodo 📘 Funding This research received no specific grant but draws on publicly available survey data.